`scipy._lib.array_api_extra._delegation:isclose`

source: /scipy/_lib/array_api_extra/_delegation.py :327

Signature

   def     isclose (    a  :  Array | complex    ,    b  :  Array | complex    ,  * ,     rtol  :  float    =  1e-05   ,    atol  :  float    =  1e-08   ,    equal_nan  :  bool    =  False   ,    xp  :  ModuleType | None    =  None     )   →  Array

Summary

Return a boolean array where two arrays are element-wise equal within a tolerance.

Extended Summary

The tolerance values are positive, typically very small numbers. The relative difference (rtol * abs(b)) and the absolute difference atol are added together to compare against the absolute difference between a and b.

NaNs are treated as equal if they are in the same place and if equal_nan=True. Infs are treated as equal if they are in the same place and of the same sign in both arrays.

Parameters

a, b : Array | int | float | complex | bool: Input objects to compare. At least one must be an array.
rtol : array_like, optional: The relative tolerance parameter (see Notes).
atol : array_like, optional: The absolute tolerance parameter (see Notes).
equal_nan : bool, optional: Whether to compare NaN's as equal. If True, NaN's in a will be considered equal to NaN's in b in the output array.
xp : array_namespace, optional: The standard-compatible namespace for a and b. Default: infer.

Returns

: Array: A boolean array of shape broadcasted from a and b, containing True where a is close to b, and False otherwise.

Warnings

The default atol is not appropriate for comparing numbers with magnitudes much smaller than one (see notes).

Notes

For finite values, isclose uses the following equation to test whether two floating point values are equivalent

absolute(a - b) <= (atol + rtol * absolute(b))

Unlike the built-in math.isclose, the above equation is not symmetric in a and b, so that isclose(a, b) might be different from isclose(b, a) in some rare cases.

The default value of atol is not appropriate when the reference value b has magnitude smaller than one. For example, it is unlikely that a = 1e-9 and b = 2e-9 should be considered "close", yet isclose(1e-9, 2e-9) is True with default settings. Be sure to select atol for the use case at hand, especially for defining the threshold below which a non-zero value in a will be considered "close" to a very small or zero value in b.

The comparison of a and b uses standard broadcasting, which means that a and b need not have the same shape in order for isclose(a, b) to evaluate to True.

isclose is not defined for non-numeric data types. bool is considered a numeric data-type for this purpose.

Aliases

scipy.differentiate.xpx.isclose